fix: Fixed few `docstrings` according to the Google Style Guide (#7717)

Fixed few docstrings according to the Google Style Guide.

examples/advanced_diffusion_training/train_dreambooth_lora_sd15_advanced.py

@@ -981,7 +981,7 @@ def collate_fn(examples, with_prior_preservation=False):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py

@@ -1136,7 +1136,7 @@ def collate_fn(examples, with_prior_preservation=False):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

examples/community/stable_diffusion_reference.py

@@ -78,7 +78,7 @@ def torch_dfs(model: torch.nn.Module):
 class StableDiffusionReferencePipeline(
     DiffusionPipeline, TextualInversionLoaderMixin, LoraLoaderMixin, IPAdapterMixin, FromSingleFileMixin
 ):
-    r""" "
+    r"""
     Pipeline for Stable Diffusion Reference.
 
     This model inherits from [`DiffusionPipeline`]. Check the superclass documentation for the generic methods

examples/custom_diffusion/train_custom_diffusion.py

@@ -152,7 +152,7 @@ def collate_fn(examples, with_prior_preservation):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

examples/dreambooth/train_dreambooth.py

@@ -742,7 +742,7 @@ def collate_fn(examples, with_prior_preservation=False):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

examples/dreambooth/train_dreambooth_flax.py

@@ -301,7 +301,7 @@ class DreamBoothDataset(Dataset):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

examples/dreambooth/train_dreambooth_lora.py

@@ -680,7 +680,7 @@ def collate_fn(examples, with_prior_preservation=False):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

examples/dreambooth/train_dreambooth_lora_sdxl.py

@@ -903,7 +903,7 @@ def collate_fn(examples, with_prior_preservation=False):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

examples/research_projects/colossalai/train_dreambooth_colossalai.py

@@ -327,7 +327,7 @@ class DreamBoothDataset(Dataset):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

examples/research_projects/dreambooth_inpaint/train_dreambooth_inpaint.py

@@ -385,7 +385,7 @@ class DreamBoothDataset(Dataset):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

examples/research_projects/dreambooth_inpaint/train_dreambooth_inpaint_lora.py

@@ -384,7 +384,7 @@ class DreamBoothDataset(Dataset):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

examples/research_projects/scheduled_huber_loss_training/dreambooth/train_dreambooth.py

@@ -762,7 +762,7 @@ def collate_fn(examples, with_prior_preservation=False):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

examples/research_projects/scheduled_huber_loss_training/dreambooth/train_dreambooth_lora.py

@@ -700,7 +700,7 @@ def collate_fn(examples, with_prior_preservation=False):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

examples/research_projects/scheduled_huber_loss_training/dreambooth/train_dreambooth_lora_sdxl.py

@@ -922,7 +922,7 @@ def collate_fn(examples, with_prior_preservation=False):
 
 
 class PromptDataset(Dataset):
-    "A simple dataset to prepare the prompts to generate class images on multiple GPUs."
+    """A simple dataset to prepare the prompts to generate class images on multiple GPUs."""
 
     def __init__(self, prompt, num_samples):
         self.prompt = prompt

src/diffusers/pipelines/animatediff/pipeline_output.py

@@ -13,7 +13,7 @@ class AnimateDiffPipelineOutput(BaseOutput):
     r"""
      Output class for AnimateDiff pipelines.
 
-     Args:
+    Args:
          frames (`torch.Tensor`, `np.ndarray`, or List[List[PIL.Image.Image]]):
              List of video outputs - It can be a nested list of length `batch_size,` with each sub-list containing
              denoised

src/diffusers/pipelines/i2vgen_xl/pipeline_i2vgen_xl.py

@@ -76,7 +76,7 @@ class I2VGenXLPipelineOutput(BaseOutput):
     r"""
      Output class for image-to-video pipeline.
 
-     Args:
+    Args:
          frames (`torch.Tensor`, `np.ndarray`, or List[List[PIL.Image.Image]]):
              List of video outputs - It can be a nested list of length `batch_size,` with each sub-list containing
              denoised

src/diffusers/pipelines/ledits_pp/pipeline_leditspp_stable_diffusion.py

@@ -1216,7 +1216,7 @@ class LEditsPPPipelineStableDiffusion(
         Paper](https://arxiv.org/abs/2301.12247). If the scheduler is set to [`~schedulers.DDIMScheduler`] the
         inversion proposed by [edit-friendly DPDM](https://arxiv.org/abs/2304.06140) will be performed instead.
 
-         Args:
+        Args:
             image (`PipelineImageInput`):
                 Input for the image(s) that are to be edited. Multiple input images have to default to the same aspect
                 ratio.

src/diffusers/pipelines/ledits_pp/pipeline_leditspp_stable_diffusion_xl.py

@@ -1449,7 +1449,7 @@ class LEditsPPPipelineStableDiffusionXL(
         Paper](https://arxiv.org/abs/2301.12247). If the scheduler is set to [`~schedulers.DDIMScheduler`] the
         inversion proposed by [edit-friendly DPDM](https://arxiv.org/abs/2304.06140) will be performed instead.
 
-         Args:
+        Args:
             image (`PipelineImageInput`):
                 Input for the image(s) that are to be edited. Multiple input images have to default to the same aspect
                 ratio.

src/diffusers/pipelines/shap_e/renderer.py

@@ -844,7 +844,7 @@ class ShapERenderer(ModelMixin, ConfigMixin):
         transmittance(t[i + 1]) := transmittance(t[i]). 4) The last term is integration to infinity (e.g. [t[-1],
         math.inf]) that is evaluated by the void_model (i.e. we consider this space to be empty).
 
-        args:
+        Args:
             rays: [batch_size x ... x 2 x 3] origin and direction. sampler: disjoint volume integrals. n_samples:
             number of ts to sample. prev_model_outputs: model outputs from the previous rendering step, including
 

src/diffusers/pipelines/text_to_video_synthesis/pipeline_output.py

@@ -15,7 +15,7 @@ class TextToVideoSDPipelineOutput(BaseOutput):
     """
      Output class for text-to-video pipelines.
 
-     Args:
+    Args:
          frames (`torch.Tensor`, `np.ndarray`, or List[List[PIL.Image.Image]]):
              List of video outputs - It can be a nested list of length `batch_size,` with each sub-list containing
              denoised